Review: Livestock disease resilience: from individual to herd level

Detection of genetic variability in dairy cattle infectivity for bovine tuberculosis

This study investigated the genetics of bovine tuberculosis (bTB) infectivity in Holstein-Friesian dairy cows using British national data. The analyses included cows with recorded sires from herds affected by bTB outbreaks between 2000 and 2022. Animals were considered bTB positive if they reacted positively to the skin test, had positive postmortem findings, or both. We introduced the "index case approach," based on the assumption that once the initial positively tested animals (index cases) are detected in a herd, subsequent infections (secondary cases) in the early stages of the breakdown are likely to be attributed to these animals. Genetic analysis of the number of secondary cases (NrSC) associated with a given index case was used to establish evidence of genetic variability in bTB infectivity of cattle, and derive EBV for infectivity for the sires of the index cases. Data were analyzed by employing Markov chain Monte Carlo techniques to fit generalized linear mixed models with either Poisson, zero-inflated Poisson (ZIP), hurdle Poisson, or geometric distributions. All 4 models demonstrated presence of genetic variance in cattle infectivity, with the strongest evidence provided by the ZIP and hurdle Poisson models. The hurdle Poisson model offered the most accurate and least biased predictions. Sire infectivity EBV from the Poisson, ZIP, and geometric models showed strong concordance, with pairwise correlations of 0.90 or higher. In contrast, correlations between EBV from the hurdle Poisson model and the other models ranged from 0.36 to 0.39. The association of the sire infectivity EBV with the average observed NrSC per sire and the proportion of infectious index case daughters per sire was generally moderate with correlations between 44% and 47% and 65% to 69%, respectively. Agreement among models for identifying the genetically most infectious sires was also reasonable, with 151 out of 285 sires appearing in the top 10% across models, and 122 (42.8%) also aligning with the top 10% based on observed average NrSC. Results provide novel evidence for exploitable genetic variance in bTB infectivity allowing the derivation of meaningful EBV. Based on the estimated posterior mean genetic variances obtained, reduction in infectivity by 1 genetic SD would result in a 32% to 44% decrease in the expected NrSC per index case. Further research is warranted to refine the phenotypic definition of infectivity and assess correlation with other dairy traits.

SIRE 2.0: a novel method for estimating polygenic host effects underlying infectious disease transmission, and analytical expressions for prediction accuracies

BACKGROUND

Genetic selection of individuals that are less susceptible to infection, less infectious once infected, and recover faster, offers an effective and long-lasting solution to reduce the incidence and impact of infectious diseases in farmed animals. However, computational methods for simultaneously estimating genetic parameters for host susceptibility, infectivity and recoverability from real-word data have been lacking. Our previously developed methodology and software tool SIRE 1.0 (Susceptibility, Infectivity and Recoverability Estimator) allows estimation of host genetic effects of a single nucleotide polymorphism (SNP), or other fixed effects (e.g. breed, vaccination status), for these three host traits using individual disease data typically available from field studies and challenge experiments. SIRE 1.0, however, lacks the capability to estimate genetic parameters for these traits in the likely case of underlying polygenic control.

RESULTS

This paper introduces novel Bayesian methodology and a new software tool SIRE 2.0 for estimating polygenic contributions (i.e. variance components and additive genetic effects) for host susceptibility, infectivity and recoverability from temporal epidemic data, assuming that pedigree or genomic relationships are known. Analytical expressions for prediction accuracies (PAs) for these traits are derived for simplified scenarios, revealing their dependence on genetic and phenotypic variances, and the distribution of related individuals within and between contact groups. PAs for infectivity are found to be critically dependent on the size of contact groups. Validation of the methodology with data from simulated epidemics demonstrates good agreement between numerically generated PAs and analytical predictions. Genetic correlations between infectivity and other traits substantially increase trait PAs. Incomplete data (e.g. time censored or infrequent sampling) generally yield only small reductions in PAs, except for when infection times are completely unknown, which results in a substantial reduction.

CONCLUSIONS

The method presented can estimate genetic parameters for host susceptibility, infectivity and recoverability from individual disease records. The freely available SIRE 2.0 software provides a valuable extension to SIRE 1.0 for estimating host polygenic effects underlying infectious disease transmission. This tool will open up new possibilities for analysis and quantification of genetic determinates of disease dynamics.

Big Six: Vertebrate host interactions as significant transmission drivers of bovine trypanosomosis in Nigeria - A systematic review and meta-analysis

Bovine trypanosomosis remains a significant challenge in Nigeria due to the widespread presence of tsetse and biting flies. Despite numerous control interventions, livestock owners continue to face the burden of high treatment costs year-round. Holistic management has been elusive, largely due to the interconnected roles of the "Big-Six" animal hosts in sustaining transmission dynamics. This study conducted a systematic review of publications from Web of Science, Ovid MEDLINE, PubMed, Google Scholar, and AJOL Online databases, following PRISMA guidelines between 2000 and 2024. Eligible studies reported trypanosomosis prevalence in cattle, small ruminants, dogs, pigs, camels, and wildlife. Subgroup analyses by breed, sex, and diagnostic techniques were performed, with point estimates evaluated at a 95 % confidence interval (CI). A total of 80 studies involving 25,171 animals were included, revealing average prevalence of 38.2 % (95 % CI: 31.4-45.3) in wildlife, pooled prevalence of 12.0 % (95 % CI: 3.0-25.1) in cattle, with 11.7 % specifically observed in trypanotolerant cattle breeds, 4.6 % (2.3-7.6) in small ruminants, 9.6 % (95 % CI: 1.9-21.5) in dogs, 10.4 % (95 % CI: 5.6-16.3) in pigs, and 28.0 % (95 % CI: 18.5-38.6) in camels. Wildlife exhibited distinct ecological patterns, while ovine and caprine data clustered closely. These findings explain the critical role of vertebrate hosts, along with bovine herd management practices, in perpetuating disease transmission within susceptible cattle populations. Effective control requires treating vertebrate hosts harbouring trypanosomes within or surrounding bovine herds and the use of insecticide-impregnated nets, alongside fencing cattle herds from forest edges. This integrated approach is essential to achieving the elimination of African animal trypanosomosis (AAT) in Nigeria and across Africa.

We Can Optimize Protein Nutrition and Reduce Nitrogen Waste in Global Pig and Food Production Systems by Adopting Circular, Sustainable, and One Health Practices

We have exceeded the Earth's carrying capacity to manage the amount of nitrogen (N) waste being generated globally, which can have devastating environmental consequences if immediate action is not taken. Our global food system is a major N user and contributor to N waste. Pork is the most consumed animal-derived protein source in the world, but like other food-producing animals, the N use efficiency of converting dietary protein to edible lean meat is <50%. However, the undigested dietary N is excreted in manure can be recycled by using appropriate manure storage and application methods to crop land to prevent further N losses and emissions to the environment. Therefore, feed and manure, along with animal health and mortality, are the main contributors to N use efficiency in pig production systems. Practical approaches to reduce N losses and emissions to the environment from pig production must be focused on fine-tuning dietary amino acid concentrations to match individual pig requirements, optimizing feed ingredient resource use, upcycling agri-industrial by-products and appropriate sources of food loss and waste, improving manure management, and maintaining pig health.

Application of Genomic Selection in Beef Cattle Disease Prevention

Genomic applications in beef cattle disease prevention have gained traction in recent years, offering new strategies for improving herd health and reducing economic losses in the livestock industry. Advances in genomics, including identification of genetic markers linked to disease resistance, provide powerful tools for early detection, selection, and management of cattle resistant to infectious diseases. By incorporating genomic technologies such as whole-genome sequencing, genotyping, and transcriptomics, researchers can identify specific genetic variants associated with resistance to pathogens like bovine respiratory disease and Johne's disease. These genomic insights allow for more accurate breeding programs aimed at enhancing disease resistance and overall herd resilience. Genomic selection, in particular, enables identification of individuals with superior genetic traits for immune function, reducing the need for antibiotic treatments and improving animal welfare. Moreover, precision medicine, powered by genomic data, supports development of tailored health management strategies, including targeted vaccination plans and antimicrobial stewardship. Incorporation of genomic tools in beef cattle management also offers the potential for early disease detection, facilitating proactive interventions that reduce the spread of infections. Despite challenges like cost, data interpretation and integration into current management systems, the potential advantages of genomic applications in disease prevention are substantial. As these technologies advance, they are anticipated to have crucial roles in improving sustainability (by enhancing herd performance), profitability (by improving overall herd longevity), and biosecurity (by decreasing the likelihood of disease outbreaks) of beef cattle production systems worldwide.

Selection for Resilience in Livestock Production Systems

Selective breeding for improved animal resilience is becoming critical to increase the sustainability of production systems. Despite the existence of a genetic component for resilience, breeding for improved resilience has been limited by the absence of a consensus on its definition and quantifying method. In this work, we provide a review of (i) the definition of resilience and related concepts such as robustness, resistance, and tolerance; (ii) possible quantifying methods for resilience; (iii) its genetic background; and (iv) insights about its improvement through selective breeding. We suggest that a resilient animal may be defined as an individual that is able to cope with a perturbation(s) and rapidly bounce back to normal functioning if altered. Furthermore, since challenging conditions lead to trade-offs and, consequently, deviations between basic physiological functions, we suggest using these deviations as indicators for resilience. These resilience indicators may also be used as proxies to study the genetic determinism and background of resilience in livestock species. Finally, we discuss possible strategies to improve resilience and review the implementation of associated genetic markers for resilience indicators in selection schemes.

Genotype-by-environment interactions in beef and dairy cattle populations: A review of methodologies and perspectives on research and applications

Modern livestock production systems are characterized by a greater focus on intensification, involving managing larger numbers of animals to achieve higher productive efficiency and animal health and welfare within herds. Therefore, animal breeding programs need to be strategically designed to select animals that can effectively enhance production performance and animal welfare across a range of environmental conditions. Thus, this review summarizes the main methodologies used for assessing the levels of genotype-by-environment interaction (G × E) in cattle populations. In addition, we explored the importance of integrating genomic and phenotypic information to quantify and account for G × E in breeding programs. An overview of the structure of cattle breeding programs is provided to give insights into the potential outcomes and challenges faced when considering G × E to optimize genetic gains in breeding programs. The role of nutrigenomics and its impact on gene expression related to metabolism in cattle are also discussed, along with an examination of current research findings and their potential implications for future research and practical applications. Out of the 116 studies examined, 60 and 56 focused on beef and dairy cattle, respectively. A total of 83.62% of these studies reported genetic correlations across environmental gradients below 0.80, indicating the presence of G × E. For beef cattle, 69.33%, 24%, 2.67%, 2.67%, and 1.33% of the studies evaluated growth, reproduction, carcass and meat quality, survival, and feed efficiency traits, respectively. By contrast, G × E research in dairy cattle populations predominantly focused on milk yield and milk composition (79.36% of the studies), followed by reproduction and fertility (19.05%), and survival (1.59%) traits. The importance of G × E becomes particularly evident when considering complex traits such as heat tolerance, disease resistance, reproductive performance, and feed efficiency, as highlighted in this review. Genomic models provide a valuable avenue for studying these traits in greater depth, allowing for the identification of candidate genes and metabolic pathways associated with animal fitness, adaptation, and environmental efficiency. Nutrigenetics and nutrigenomics are emerging fields that require extensive investigation to maximize our understanding of gene-nutrient interactions. By studying various transcription factors, we can potentially improve animal metabolism, improving performance, health, and quality of products such as meat and milk.

Advancing mastitis assessment in dairy bovines via short milking tube thermography: A seasonal perspective

In India, where dairy production leads globally, infrared thermography (IRT) and short milking tube thermography specifically are vital for managing mastitis. Therefore, the present study focuses on thermal imaging of the udder and short milking tube (SMT) of the milking machine during the peak milking process of Sahiwal cows and Murrah buffaloes during winter, summer, rainy and autumn seasons to identify sub-clinical (SCM) and clinical mastitis (CM) cases using the Darvi DTL007 camera. The udder health was assessed using the California Mastitis Test, Somatic Cell Count (SCC) and IRT throughout the year. Log10SCC and thermogram analysis revealed a difference (p < 0.01) between healthy, SCM, and CM cases during different seasons in both breeds. Further results showed an increase (p < 0.01) in SMT thermograms of SCM and CM cases compared to healthy quarters in Sahiwal cows during winter, summer, rainy, and autumn were 4.26 and 7.51, 2.37 and 4.47, 2.20 and 3.64, 2.90 and 4.94 ºC, respectively and for Murrah buffaloes were 3.56 and 5.55, 2.70 and 3.81, 1.72 and 3.10, 3.14 and 4.42ºC, respectively. The highest degree of increase in milking udder skin surface temperature and SMT of SCM and CM cases compared to healthy quarters was observed during the winter and the least during the rainy season. Thus, regardless of the seasons examined in this study, SMT thermograms effectively assessed SCM and CM.

Getting to grips with resilience: Toward large-scale phenotyping of this complex trait

The capacity of animals to cope with environmental perturbations, hereafter called resilience, is an increasingly important trait. Resilience at the level of the animal is an emergent property of multiple underlying mechanisms (physiological, immunological, behavioral). This means that there is no direct measure of resilience, no easy key traits. Resilience is a latent variable that may be inferred from multivariate measures. Further, the flexibility that resilience provides is evidenced in the rate of response to, and rate of recovery from, the environmental perturbation. Thus, it requires time-series measurements. The increasing availability of on-farm precision livestock technologies, which are capable of providing time-series measures of performance and of various physiological and health biomarkers, offer the opportunity to move toward large-scale phenotyping of resilience. There have been numerous studies putting forward methods to quantify resilience. These methods can be classified as being data driven or concept driven. However, new candidate resilience proxies need to be validated. This is tricky to do because there is no direct measure of resilience, no easy gold standard measure. Per definition, good resilience will benefit the animal. Thus, the accumulated consequences of resilience can be used to evaluate resilience proxies. All other things being equal, it is expected that good resilience will be associated with a longer functional longevity (longevity adjusted for production level), with more reproductive cycles, and with fewer disease events. Recent examples of this approach of evaluating resilience proxies against the accumulated consequences of resilience are discussed. They show clearly that operational resilience proxies that are heritable and have been validated against the consequences of good resilience can be derived from on-farm time-series data. With the aim of deriving more nuanced phenotypes, there are an increasing number of studies that have taken up the challenge of attempting to statistically combine the information coming from multiple time-series measures. These studies show how multivariate time-series statistics can be used to derive more nuanced resilience phenotypes that capture some of the underlying mechanisms of resilience. In conclusion, the recent studies reviewed here have shown that operational and heritable resilience proxies exist, that they can form the basis for selection for resilience, and that more nuanced phenotypes are attainable, which will allow selection for resilience to be tailored according to prevailing environmental challenge types.

Validating statistical properties of resilience indicators derived from simulated longitudinal performance measures of farmed animals

Resilience is commonly defined as the ability of an individual to be minimally affected or to quickly recover from a challenge. Improvement of animals' resilience is a vital component of sustainable livestock production but has so far been hampered by the lack of established quantitative resilience measures. Several studies proposed that summary statistics of the deviations of an animal's observed performance from its target performance trajectory (i.e., performance in the absence of challenge) may constitute suitable quantitative resilience indicators. However, these statistical indicators require further validation. The aim of this study was to obtain a better understanding of these resilience indicators in their ability to discriminate between different response types and their dependence on different response characteristics of animals, and data recording features. To this purpose, milk-yield trajectories of individual dairy cattle differing in resilience, without and when exposed to a short-term challenge, were simulated. Individuals were categorised into three broad response types (with individual variation within each type): Fully Resilient animals, which experience no systematic perturbation in milk yield after challenge, Non-Resilient animals whose milk yield permanently deviates from the target trajectory after challenge and Partially Resilient animals that experience temporary perturbations but recover. The following statistical resilience indicators previously suggested in the literature were validated with respect to their ability to discriminate between response types and their sensitivity to various response features and data characteristics: logarithm of mean of squares (LMS), logarithm of variance (LV), skewness (S), lag-1 autocorrelation (AC1), and area under the curve (AUC) of deviations. Furthermore, different methods for estimating unknown target trajectories were evaluated. All of the considered resilience indicators could distinguish between the Fully Resilient response type and either of the other two types when target trajectories were known or estimated using a parametric method. When the comparison was between Partially Resilient and Non-Resilient, only LMS, LV, and AUC could correctly rank the response types, provided that the observation period was at least twice as long as the perturbation period. Skewness was in general the least reliable indicator, although all indicators showed correct dependency on the amplitude and duration of the perturbations. In addition, all resilience indicators except for AC1 were robust to lower frequency of measurements. In general, parametric methods (quantile or repeated regression) combined with three resilience indicators (LMS, LV and AUC) were found the most reliable techniques for ranking animals in terms of their resilience.

Dare to be resilient: the key to future pesticide-free orchards?

Considering the urgent need for more sustainable fruit tree production, it is high time to find durable alternatives to the systematic use of phytosanitary products in orchards. To this end, resilience can deliver a number of benefits. Relying on a combination of tolerance, resistance, and recovery traits, disease resilience appears as a cornerstone to cope with the multiple pest and disease challenges over an orchard's lifetime. Here, we describe resilience as the capacity of a tree to be minimally affected by external disturbances or to rapidly bounce back to normal functioning after being exposed to these disturbances. Based on a literature survey largely inspired from research on livestock, we highlight different approaches for dissecting phenotypic and genotypic components of resilience. In particular, multisite experimental designs and longitudinal measures of so-called 'resilience biomarkers' are required. We identified a list of promising biomarkers relying on ecophysiological and digital measurements. Recent advances in high-throughput phenotyping and genomics tools will likely facilitate fine scale temporal monitoring of tree health, allowing identification of resilient genotypes with the calculation of specific resilience indicators. Although resilience could be considered as a 'black box' trait, we demonstrate how it could become a realistic breeding goal.

Integration of selective sweeps across the sheep genome: understanding the relationship between production and adaptation traits

BACKGROUND

Livestock populations are under constant selective pressure for higher productivity levels for different selective purposes. This pressure results in the selection of animals with unique adaptive and production traits. The study of genomic regions associated with these unique characteristics has the potential to improve biological knowledge regarding the adaptive process and how it is connected to production levels and resilience, which is the ability of an animal to adapt to stress or an imbalance in homeostasis. Sheep is a species that has been subjected to several natural and artificial selective pressures during its history, resulting in a highly specialized species for production and adaptation to challenging environments. Here, the data from multiple studies that aim at mapping selective sweeps across the sheep genome associated with production and adaptation traits were integrated to identify confirmed selective sweeps (CSS).

RESULTS

In total, 37 studies were used to identify 518 CSS across the sheep genome, which were classified as production (147 prodCSS) and adaptation (219 adapCSS) CSS based on the frequency of each type of associated study. The genes within the CSS were associated with relevant biological processes for adaptation and production. For example, for adapCSS, the associated genes were related to the control of seasonality, circadian rhythm, and thermoregulation. On the other hand, genes associated with prodCSS were related to the control of feeding behaviour, reproduction, and cellular differentiation. In addition, genes harbouring both prodCSS and adapCSS showed an interesting association with lipid metabolism, suggesting a potential role of this process in the regulation of pleiotropic effects between these classes of traits.

CONCLUSIONS

The findings of this study contribute to a deeper understanding of the genetic link between productivity and adaptability in sheep breeds. This information may provide insights into the genetic mechanisms that underlie undesirable genetic correlations between these two groups of traits and pave the way for a better understanding of resilience as a positive ability to respond to environmental stressors, where the negative effects on production level are minimized.

Survey of Animal Neoplastic Cases Diagnosed in Nigerian Veterinary Teaching Hospitals, 2000-2017

Incidence data from 17-year veterinary neoplasm surveillance and registration were reviewed. Most of the neoplastic cases diagnosed in Nigerian veterinary teaching hospitals (VTHs) were in the avian (49%) and canine species (44%). Fewer cases were recorded in the equine (3.2%), bovine (2.4%), ovine (1.5%), caprine (0.3%) and porcine (0.15%) species. Marek's disease was the most prevalently diagnosed neoplastic disease of domestic animals in Nigerian VTHs from 2000-2017. Also, the Nigerian local breed had a higher mean distribution than any other dog breed and this was statistically significant (p < 0.05). Nearly all of the neoplastic cases diagnosed, were found in females (60.4%) and so the mean distribution of sex was statistically significant (p < 0.05). The digestive system, with 296 (46.25%) cases, was the anatomic location where the majority of the neoplastic cases were found. However, the mean distribution of different neoplastic anatomic sites was not statistically significant (p > 0.05). In conclusion, little emphasis is given to the appropriate diagnosis and recording of neoplastic cases that are diagnosed. The study provides information regarding the prevalence and distribution of tumours in different animal species consulted in Nigeria veterinary teaching hospitals. To illustrate all of this, ArcGIS software was used. Veterinary clinicians, pathologists and epidemiologists from Nigeria may benefit from the results of this study by freely accessing some specific data regarding the breed, the age group or the gender of some animal species diagnosed with different tumours.

Disease resistance and infectivity of virus susceptible and resistant common carp strains

Infectious diseases challenge health and welfare of humans and animals. Unlike for humans, breeding of genetically resistant animals is a sustainable solution, also providing unique research opportunities. Chances to survive a disease are improved by disease resistance, but depend also on chances to get infected and infect others. Considerable knowledge exists on chances of susceptible and resistant animals to survive a disease, yet, almost none on their infectivity and if and how resistance and infectivity correlate. Common carp (Cyprinus carpio) is widely produced in aquaculture, suffering significantly from a disease caused by cyprinid herpes virus type 3 (CyHV-3). Here, the infectivity of disease-resistant and susceptible fish types was tested by playing roles of shedders (infecting) and cohabitants (infected) in all four type-role combinations. Resistant shedders restricted spleen viral load and survived more than susceptible ones. However, mortality of susceptible cohabitants infected by resistant shedders was lower than that of resistant cohabitants infected by susceptible shedders. Virus levels in water were lower in tanks with resistant shedders leading to lower spleen viral loads in cohabitants. Thus, we empirically demonstrated that disease resistant fish survive better and infect less, with implications to epidemiology in general and to the benefit of aquaculture production.

Advances in understanding the genetic architecture of antibody response to paratuberculosis in sheep by heritability estimate and LDLA mapping analyses and investigation of candidate regions using sequence-based data

BACKGROUND

Paratuberculosis is a contagious and incurable disease that is caused by Mycobacterium avium subsp. paratuberculosis (MAP) with significant negative effects on animal welfare and farm profitability. Based on a large naturally infected flock over 12 years, we analyzed repeated enzyme-linked immunosorbent assay tests (ELISA), OvineSNP50 BeadChip genotypes and whole-genome sequences imputed from 56 influential animals. The main goals were to estimate the genetic parameters of proxy traits for resistance to MAP, identify genomic regions associated with the host's immune response against MAP and search for candidate genes and causative mutations through association and functional annotation analyses of polymorphisms identified by sequencing.

RESULTS

Two variables were derived from ELISA tests. The first, a binary variable, assessed the infection status of each animal over the entire productive life, while the second considered the level of antibody recorded over time. Very similar results were obtained for both variables. Heritability estimates of about 0.20 were found and a significant region capturing 18% and 13% of the genetic variance was detected on ovine chromosome 20 by linkage disequilibrium and linkage analysis on OvineSNP50 positions. Functional annotation and association analyses on the imputed sequence polymorphisms that were identified in this region were carried out. No significant variants showed a functional effect on the genes that mapped to this region, most of which belong to the major histocompatibility complex class II (MHC II). However, the conditional analysis led to the identification of two significant polymorphisms that can explain the genetic variance associated with the investigated genomic region.

CONCLUSIONS

Our results confirm the involvement of the host's genetics in susceptibility to MAP in sheep and suggest that selective breeding may be an option to limit the infection. The estimated heritability is moderate with a relevant portion being due to a highly significant region on ovine chromosome 20. The results of the combined use of sequence-based data and functional analyses suggest several genes belonging to the MHC II as the most likely candidates, although no mutations in their coding regions showed a significant association. Nevertheless, information from genotypes of two highly significant polymorphisms in the region can enhance the efficiency of selective breeding programs.

Genetics and Genomics of Infectious Diseases in Key Aquaculture Species

Diseases pose a significant and pressing concern for the sustainable development of the aquaculture sector, particularly as their impact continues to grow due to climatic shifts such as rising water temperatures. While various approaches, ranging from biosecurity measures to vaccines, have been devised to combat infectious diseases, their efficacy is disease and species specific and contingent upon a multitude of factors. The fields of genetics and genomics offer effective tools to control and prevent disease outbreaks in aquatic animal species. In this study, we present the key findings from our recent research, focusing on the genetic resistance to three specific diseases: White Spot Syndrome Virus (WSSV) in white shrimp, Bacterial Necrotic Pancreatitis (BNP) in striped catfish, and skin fluke (a parasitic ailment) in yellowtail kingfish. Our investigations reveal that all three species possess substantial heritable genetic components for disease-resistant traits, indicating their potential responsiveness to artificial selection in genetic improvement programs tailored to combat these diseases. Also, we observed a high genetic association between disease traits and survival rates. Through selective breeding aimed at enhancing resistance to these pathogens, we achieved substantial genetic gains, averaging 10% per generation. These selection programs also contributed positively to the overall production performance and productivity of these species. Although the effects of selection on immunological traits or immune responses were not significant in white shrimp, they yielded favorable results in striped catfish. Furthermore, our genomic analyses, including shallow genome sequencing of pedigreed populations, enriched our understanding of the genomic architecture underlying disease resistance traits. These traits are primarily governed by a polygenic nature, with numerous genes or genetic variants, each with small effects. Leveraging a range of advanced statistical methods, from mixed models to machine and deep learning, we developed prediction models that demonstrated moderate-to-high levels of accuracy in forecasting these disease-related traits. In addition to genomics, our RNA-seq experiments identified several genes that undergo upregulation in response to infection or viral loads within the populations. Preliminary microbiome data, while offering limited predictive accuracy for disease traits in one of our studied species, underscore the potential for combining such data with genome sequence information to enhance predictive power for disease traits in our populations. Lastly, this paper briefly discusses the roles of precision agriculture systems and AI algorithms and outlines the path for future research to expedite the development of disease-resistant genetic lines tailored to our target species. In conclusion, our study underscores the critical role of genetics and genomics in fortifying the aquaculture sector against the threats posed by diseases, paving the way for more sustainable and resilient aquaculture development.

New insights in improving sustainability in meat production: opportunities and challenges

Treating livestock as senseless production machines has led to rampant depletion of natural resources, enhanced greenhouse gas emissions, gross animal welfare violations, and other ethical issues. It has essentially instigated constant scrutiny of conventional meat production by various experts and scientists. Sustainably in the meat sector is a big challenge which requires a multifaced and holistic approach. Novel tools like digitalization of the farming system and livestock market, precision livestock farming, application of remote sensing and artificial intelligence to manage production and environmental impact/GHG emission, can help in attaining sustainability in this sector. Further, improving nutrient use efficiency and recycling in feed and animal production through integration with agroecology and industrial ecology, improving individual animal and herd health by ensuring proper biosecurity measures and selective breeding, and welfare by mitigating animal stress during production are also key elements in achieving sustainability in meat production. In addition, sustainability bears a direct relationship with various social dimensions of meat production efficiency such as non-market attributes, balance between demand and consumption, market and policy failures. The present review critically examines the various aspects that significantly impact the efficiency and sustainability of meat production.

The evolution of parasite virulence under targeted culling and harvesting in wildlife and livestock

There is a clear need to understand the effect of human intervention on the evolution of infectious disease. In particular, culling and harvesting of both wildlife and managed livestock populations are carried out in a wide range of management practices, and they have the potential to impact the evolution of a broad range of disease characteristics. Applying eco-evolutionary theory we show that once culling/harvesting becomes targeted on specific disease classes, the established result that culling selects for higher virulence is only found when sufficient infected individuals are culled. If susceptible or recovered individuals are targeted, selection for lower virulence can occur. An important implication of this result is that when culling to eradicate an infectious disease from a population, while it is optimal to target infected individuals, the consequent evolution can increase the basic reproductive ratio of the infection, R 0 , and make parasite eradication more difficult. We show that increases in evolved virulence due to the culling of infected individuals can lead to excess population decline when sustainably harvesting a population. In contrast, culling susceptible or recovered individuals can select for decreased virulence and a reduction in population decline through culling. The implications to the evolution of virulence are typically the same in wildlife populations, that are regulated by the parasite, and livestock populations, that have a constant population size where restocking balances the losses due to mortality. However, the well-known result that vertical transmission selects for lower virulence and transmission in wildlife populations is less marked in livestock populations for parasites that convey long-term immunity since restocking can enhance the density of the immune class. Our work emphasizes the importance of understanding the evolutionary consequences of intervention strategies and the different ecological feedbacks that can occur in wildlife and livestock populations.

Abortion and fetal death in sows

Abortion in sows or the expulsion of foetuses between days 35 and 109 of gestation results in major financial losses. Abortion is the result of maternal failure due to factors interfering with either the endocrine control of pregnancy or causing endometrial damage. In addition, causes of fetal origin, due to infections with a special affinity for the fetus, can also lead to abortion. Many different non-infectious and infectious factors may be involved. Non-infectious risk factors include inappropriate ambient temperature, seasonal effects, different stress factors, and toxic substances. Microorganisms that may cause abortion can be classified as facultative pathogenic and specific pathogenic microorganisms. The first category includes mostly bacteria that are endemic in many pig farms and that are normally harmless commensals. They can cause abortion only in case of decreased immunity or other predisposing factors. Different specific pathogenic microorganisms, especially viruses and bacteria, can cause fetal death and abortion. Some may have a special affinity for the reproductive tract and the foetuses (e.g. Aujeszky's disease virus, parvovirus, Leptospira sp.), while others may cause clinical disease or fever in sows (e.g. swine influenza viruses, Erysipelothrix rhusiopathiae), subsequently leading to abortion. Diagnosis of fetal death and abortion is challenging due to the broad array of processes that may be involved, and the fact that the inciting cause may happen well in advance of the abortion. The diagnostic process should start with a thorough evaluation of the clinical problem and the farm. In case an infectious cause is suspected, proper samples should be collected, preferably from different sows and foetuses, for the detection of specific pathogens. Prevention of abortion mainly relies on the implementation of good management practices, hygiene and biosecurity measures, and for some pathogens also on vaccination.

The WUR0000125 PRRS resilience SNP had no apparent effect on pigs' infectivity and susceptibility in a novel transmission trial

BACKGROUND

Porcine reproductive and respiratory syndrome (PRRS) remains one of the most important infectious diseases for the pig industry. A novel small-scale transmission experiment was designed to assess whether the WUR0000125 (WUR for Wageningen University and Research) PRRS resilience single nucleotide polymorphism (SNP) confers lower susceptibility and infectivity to pigs under natural porcine reproductive and respiratory syndrome virus (PRRSV-2) transmission.

METHODS

Commercial full- and half-sib piglets (n = 164) were assigned as either Inoculation, Shedder, or Contact pigs. Pigs were grouped according to their relatedness structure and WUR genotype, with R- and R+ referring to pigs with zero and one copy of the dominant WUR resilience allele, respectively. Barcoding of the PRRSV-2 strain (SD09-200) was applied to track pig genotype-specific transmission. Blood and nasal swab samples were collected and concentrations of PRRSV-2 were determined by quantitative (q)-PCR and cell culture and expressed in units of median tissue culture infectious dose (TCID₅₀). The Log₁₀TCID₅₀ at each sampling event, derived infection status, and area under the curve (AUC) were response variables in linear and generalized linear mixed models to infer WUR genotype differences in Contact pig susceptibility and Shedder pig infectivity.

RESULTS

All Shedder and Contact pigs, except one, became infected through natural transmission. There was no significant (p > 0.05) effect of Contact pig genotype on any virus measures that would indicate WUR genotype differences in susceptibility. Contact pigs tended to have higher serum AUC (p = 0.017) and log₁₀TCID₅₀ (p = 0.034) when infected by an R+ shedder, potentially due to more infectious R+ shedders at the early stages of the transmission trial. However, no significant Shedder genotype effect was found in serum (p = 0.274) or nasal secretion (p = 0.951) that would indicate genotype differences in infectivity.

CONCLUSIONS

The novel design demonstrated that it is possible to estimate genotype effects on Shedder pig infectivity and Contact pig susceptibility that are not confounded by family effects. The study, however, provided no supportive evidence that genetic selection on WUR genotype would affect PRRSV-2 transmission. The results of this study need to be independently validated in a larger trial using different PRRSV strains before dismissing the effects of the WUR marker or the previously detected GBP5 gene on PRRSV transmission.

Seroprevalence of Peste des Petits Ruminants and Contagious Caprine Pleuropneumonia Coinfections in Goats in Kwale County, Kenya

Goats are among the most important small ruminants affected by Peste des Petits ruminants (PPR) and contagious caprine pleuropneumonia (CCPP) diseases, two of the most significant constraints worldwide to the production of small ruminant species. Herein, the competitive enzyme-linked immunosorbent assay (cELISA) and the latex agglutination test (LAT) were used to determine the coinfections of PPR and CCPP in goats in Kwale County on Kenya's South Coast. A total of 368 serum samples were collected from goats of various ages and sexes exhibiting respiratory distress in the four subcounties of Kwale County (Kinango, Lunga Lunga, Matuga, and Msambweni) and screened for PPR and CCPP antibodies. Of the 368 goats sampled, 259 (70.4%) were females and 109 (29.6%) were males, and 126 (34.2%), 71 (19.3%), 108 (29.3%), and 63 (17.1%) samples were collected from Kinango, Matuga, Lunga Lunga, and Msambweni, respectively. The overall PPR seropositivity rate was 48.6% (179/368); rates in Kinango, Lunga Lunga, Matuga, and Msambweni were 70.6%, 29.6%, 49.3%, and 36.5%, respectively. The overall CCPP seropositivity rate was 45.4% (167/368), while rates in Kinango, Lunga Lunga, Matuga, and Msambweni were 51.6%, 49.1%, 36.6%, and 36.5%, respectively. Notably, the seropositivity of PPR was higher in male (53.3%) than in female (46.72%) goats, though not statistically significant. In addition, the CCPP seropositivity rates were not significantly different between male (44.0%) and female (45.9%) goats. Regarding age, the PPR seropositivity rates were 45.9%, 55.8%, and 52.3% in adults, kids, and weaners, respectively. For CCPP, the seropositivity rates were 48.3%, 40.4%, and 42.3% in adults, kids, and weaners, respectively. The coinfection rate of PPR and CCPP was 22.3% (82/368). Despite the high coinfection, univariate analysis revealed no relationship between PPR and CCPP infections. However, given the high PPR and CCPP infection rates, as a result of separate or coinfection, there is a need to upscale or intensify vaccination in the county.

Development of meat analogs: Focus on the current status and challenges of regulatory legislation

Population growth and the rising enthusiasm for meat consumption in developing countries have increased the global demand for animal protein. The limited increase in traditional meat production, which results in high resource consumption, greenhouse gas emissions, and zoonotic diseases, has affected the sustainable supply of meat protein. The technological development and commercialization of meat analogs derived from plant and microbial proteins provide a strategy for solving the abovementioned problems. However, before these innovative foods are marketed, they should comply with regulations and standards to ensure food safety and consumer rights. This review briefly summarizes the global development status and challenges of plant- and fungi-based meat analog products. It focuses on the current status, characteristics, and disputes in the regulations and standards worldwide for plant- and fungi-based meat analogs and proposes suggestions for perfecting the regulatory system from the perspective of ensuring safety and supporting innovation. Although plant- and fungi-based meat analogs have had a history of safe usage as foods for a certain period around the world, the nomenclature and product standards are uncertain, which affects product innovation and global sales. Regulatory authorities should promptly formulate and revise regulations or standards to clarify the naming of meat analogs and product standards, especially the use of animal-derived ingredients and limits of nutrients (e.g., protein, fat, vitamins, and minerals) to continuously introduce start-up products to the market.

Effects of hatching system on chick quality, welfare and health of young breeder flock offspring

Alternative hatching systems have been developed for broiler chickens to provide immediately feed and water after hatch and reduce the number or severity of early life stressors. Besides beneficial effects of these alternative hatching systems on chick quality and performance, broiler health and welfare may be positively affected as well. Especially offspring from young broiler breeder flocks may benefit, as they have been shown to be more sensitive to preturbations than offspring from older breeder flocks. This study evaluated effects of hatching systems on chick quality, health and welfare of young breeder flock offspring, using 3 different hatching systems: conventional hatchery-hatched (HH), hatchery-fed (HF), and on-farm hatching (OH). A total of 24 pens were used in a completely randomized block design, with 8 pens per hatching system and 30 chickens per pen. Chick quality at hatch and performance until 35 d of age was improved in the HF and OH compared to HH treatment, but only minor effects were found on the welfare indicators: footpad dermatitis, hock burn, cleanliness, skin lesion and gait score. No effect was observed on the dynamics of a humoral immune response after NCD vaccination, given at d 0 and 14 of age, as no differences between NCD titers were found at d 18. Animals were vaccinated with a live attenuated infectious bronchitis vaccine virus (IBV) at d 28 to address treatment related differences to disease resilience. The expressions of inflammation and epithelial integrity related genes in the trachea and histo-pathological changes in the trachea were examined at 3 d after vaccine administration. No differences between treatment groups were observed. Although beneficial effects of HF and OH systems were found for young breeder flock offspring on chick quality at hatch and body weight posthatch, only one effect of alternative hatching systems on welfare and health indicators were found. No effect of hatching system on humoral immune response or disease resilience was found.

Applying genetic technologies to combat infectious diseases in aquaculture

Disease and parasitism cause major welfare, environmental and economic concerns for global aquaculture. In this review, we examine the status and potential of technologies that exploit genetic variation in host resistance to tackle this problem. We argue that there is an urgent need to improve understanding of the genetic mechanisms involved, leading to the development of tools that can be applied to boost host resistance and reduce the disease burden. We draw on two pressing global disease problems as case studies-sea lice infestations in salmonids and white spot syndrome in shrimp. We review how the latest genetic technologies can be capitalised upon to determine the mechanisms underlying inter- and intra-species variation in pathogen/parasite resistance, and how the derived knowledge could be applied to boost disease resistance using selective breeding, gene editing and/or with targeted feed treatments and vaccines. Gene editing brings novel opportunities, but also implementation and dissemination challenges, and necessitates new protocols to integrate the technology into aquaculture breeding programmes. There is also an ongoing need to minimise risks of disease agents evolving to overcome genetic improvements to host resistance, and insights from epidemiological and evolutionary models of pathogen infestation in wild and cultured host populations are explored. Ethical issues around the different approaches for achieving genetic resistance are discussed. Application of genetic technologies and approaches has potential to improve fundamental knowledge of mechanisms affecting genetic resistance and provide effective pathways for implementation that could lead to more resistant aquaculture stocks, transforming global aquaculture.

A functional mutation associated with piglet diarrhea partially by regulating the transcription of porcine STAT3

The present study aimed to search for functional mutations within the promoter of porcine STAT3 and to provide causative genetic variants associated with piglet diarrhea. We firstly confirmed that STAT3 expressed higher in the small intestine than in the spleen, stomach and large intestine of SPF piglets, respectively (P &lt; 0.05). Then, 10 genetic variations in the porcine STAT3 promoter region was identified by direct sequencing. Among them, three mutations SNP1: g.−870 G&gt;A, SNP2: g.−584 A&gt;C and a 6-bp Indel in the promoter region that displayed significant differential transcriptional activities were identified. Association analyses showed that SNP1: g.−870 G&gt;A was significantly associated with piglet diarrhea (P &lt; 0.05) and the GG animals had lower diarrhea score than AA piglets (P &lt; 0.01) in both Min and Landrace population. Further functional analysis revealed that E2F6 repressed the transcriptional efficiency of STAT3 in vitro, by binding the G allele of SNP1. The present study suggested that SNP1: g.−870 G&gt;A was a piglet diarrhea-associated variant that directly affected binding with E2F6, leading to changes in STAT3 transcription which might partially contribute to piglet diarrhea susceptibility or resistance.

Optimal experimental designs for estimating genetic and non-genetic effects underlying infectious disease transmission

BACKGROUND

The spread of infectious diseases in populations is controlled by the susceptibility (propensity to acquire infection), infectivity (propensity to transmit infection), and recoverability (propensity to recover/die) of individuals. Estimating genetic risk factors for these three underlying host epidemiological traits can help reduce disease spread through genetic control strategies. Previous studies have identified important 'disease resistance single nucleotide polymorphisms (SNPs)', but how these affect the underlying traits is an unresolved question. Recent advances in computational statistics make it now possible to estimate the effects of SNPs on host traits from epidemic data (e.g. infection and/or recovery times of individuals or diagnostic test results). However, little is known about how to effectively design disease transmission experiments or field studies to maximise the precision with which these effects can be estimated.

RESULTS

In this paper, we develop and validate analytical expressions for the precision of the estimates of SNP effects on the three above host traits for a disease transmission experiment with one or more non-interacting contact groups. Maximising these expressions leads to three distinct 'experimental' designs, each specifying a different set of ideal SNP genotype compositions across groups: (a) appropriate for a single contact-group, (b) a multi-group design termed "pure", and (c) a multi-group design termed "mixed", where 'pure' and 'mixed' refer to groupings that consist of individuals with uniformly the same or different SNP genotypes, respectively. Precision estimates for susceptibility and recoverability were found to be less sensitive to the experimental design than estimates for infectivity. Whereas the analytical expressions suggest that the multi-group pure and mixed designs estimate SNP effects with similar precision, the mixed design is preferred because it uses information from naturally-occurring rather than artificial infections. The same design principles apply to estimates of the epidemiological impact of other categorical fixed effects, such as breed, line, family, sex, or vaccination status. Estimation of SNP effect precisions from a given experimental setup is implemented in an online software tool SIRE-PC.

CONCLUSIONS

Methodology was developed to aid the design of disease transmission experiments for estimating the effect of individual SNPs and other categorical variables that underlie host susceptibility, infectivity and recoverability. Designs that maximize the precision of estimates were derived.

The quantitative genetics of the prevalence of infectious diseases: hidden genetic variation due to indirect genetic effects dominates heritable variation and response to selection

Infectious diseases have profound effects on life, both in nature and agriculture. However, a quantitative genetic theory of the host population for the endemic prevalence of infectious diseases is almost entirely lacking. While several studies have demonstrated the relevance of transmission of infections for heritable variation and response to selection, current quantitative genetics ignores transmission. Thus, we lack concepts of breeding value and heritable variation for endemic prevalence, and poorly understand response of endemic prevalence to selection. Here, we integrate quantitative genetics and epidemiology, and propose a quantitative genetic theory for the basic reproduction number R0 and for the endemic prevalence of an infection. We first identify the genetic factors that determine the prevalence. Subsequently, we investigate the population-level consequences of individual genetic variation, for both R0 and the endemic prevalence. Next, we present expressions for the breeding value and heritable variation, for endemic prevalence and individual binary disease status, and show that these depend strongly on the prevalence. Results show that heritable variation for endemic prevalence is substantially greater than currently believed, and increases strongly when prevalence decreases, while heritability of disease status approaches zero. As a consequence, response of the endemic prevalence to selection for lower disease status accelerates considerably when prevalence decreases, in contrast to classical predictions. Finally, we show that most heritable variation for the endemic prevalence is hidden in indirect genetic effects, suggesting a key role for kin-group selection in the evolutionary history of current populations and for genetic improvement in animals and plants.